<MIMO>
In recent years, in order to achieve higher speed in wireless data communication in a limited frequency band, many kinds of research have been performed for improving frequency utilization efficiency. Among these kinds, a MIMO (multi-input multi-output) technology that simultaneously uses multiple antennas to increase the transmission capacity per unit frequency is gaining attention.
<LP MU-MIMO>
Known examples of MIMO include single-user MIMO (SU-MIMO) in which a base station (BS) transmits multiple signals at the same time and with the same frequency to a single terminal (mobile station: MS) and multi-user MIMO (MU-MIMO) in which the base station transmits signals at the same time and with the same frequency to different terminal devices.
In SU-MIMO, since the number of streams that can be multiplexed cannot be larger than the number of antennas included in a terminal device, the maximum number of streams is limited by the number of physical antennas in the terminal device. On the other hand, since the base station can have a larger number of antennas than the terminal device, MU-MIMO is also essential to make best use of antennas remaining in the base station. In LTE and LTE-Advanced, downlink (DL) MU-MIMO that uses linear precoding (LP) has already been put into practical use (see Non Patent Literature 1).
<NLP MU-MIMO>
However, with MU-MIMO that uses LP (LP MU-MIMO), the base station needs to remove multi-user interference (MUI) by multiplying linear filters to orthogonalize transmission signals, resulting in lower flexibility in terms of combinations of terminal devices that can be spatially-multiplexed.
As another method for achieving spatial multiplexing, nonlinear precoding (NLP) MU-MIMO is proposed. In NLP MU-MIMO, each terminal device performs modulo calculation in which points obtained by translating a reception signal toward an in-phase channel (I-ch) and a quadrature channel (Q-ch) by an integral multiple of a fixed width (modulo width) are regarded as the same point. Therefore, since the base station becomes capable of adding a signal (perturbation vector) corresponding to an arbitrary integral multiple of the modulo width to a modulation signal, the base station appropriately selects a perturbation vector that allows for lower transmission power and adds the perturbation vector to a signal destined for each terminal device (see Non Patent Literature 2).
<VP MU-MIMO>
When a terminal device performs modulo calculation on a reception signal, the base station becomes free to add a signal corresponding to an arbitrary integral multiple of the modulo width to each modulation signal. This addable signal is called a perturbation vector. A VP (vector perturbation) MU-MIMO method is a method of performing a full search in view of the channel states of all terminal devices that are subject to spatial multiplexing so as to find a perturbation vector that achieves the most improved power efficiency. VP MU-MIMO requires a large amount of calculation by the base station but can achieve a full transmission diversity gain, and is an NLP MU-MIMO method that exhibits extremely good characteristics (see Non Patent Literature 2).
<THP MU-MIMO>
Unlike VP MU-MIMO, THP MU-MIMO is a method of sequentially calculating perturbation vectors to be added to signals destined for the individual terminal devices in view of multi-user interference affecting each terminal device. Although THP MU-MIMO allows for lower complexity of transmission processing performed by the base station, a full transmission diversity cannot be achieved for all of the terminal devices (see Non Patent Literature 2).
<Ordering THP MU-MIMO>
Although THP MU-MIMO removes the interference affecting the terminal devices subject to spatial multiplexing in a certain order for the individual terminal devices, the characteristics can be improved by optimizing the order in which the interference is removed. One of the technologies that exhibit good characteristics is a vertical-bell laboratories space-time THP (VBLAST-THP) technology (see Non Patent Literature 3). Furthermore, as a technology for reducing the amount of calculation in VBLAST-THP, a sorted QR decomposition (SQRD) THP technology is known (see Non Patent Literature 3).
<LR-THP>
An LR-THP method is a method of adding processing called lattice reduction (LR) to THP MU-MIMO so as to achieve a full transmission diversity gain with an amount of calculation smaller than that in VP MU-MIMO. As a lattice reduction algorithm, a method that uses LLL-algorithm (Lenstra-Lenstra-Lovasz algorithm: LLLA) and a method that uses a joint quasi-orthogonalization: JQO) are proposed (see Non Patent Literature 3 and Non Patent Literature 4).
<LR-DFE>
Non Patent Literature 5 discusses a decision feedback equalizer (DFE) using LR in SU-MIMO, that is, LR-DFE. Although LR-DFE is a technology for the reception side, it is also an equalization technology of sequentially performing signal detection after performing LR, and filter calculation processing is similar to LR-THP. LR-DFE is a technology that improves the characteristics by performing DFE in the related art after enhancing the orthogonality of a channel matrix by LR at the reception side (see Non Patent Literature 5).
<SQRD-LLLA>
Although LLLA is often used in LR commonly used for LR-THP and LR-DFE, SQRD-LLLA is known as an algorithm proposed as a method for reducing the amount of calculation in this LLLA. In SQRD-LLLA, sorted QR decomposition (SQRD) is performed on a channel matrix, which indicates a MIMO channel, before performing LLLA. In this case, SQRD is an algorithm that decomposes a channel matrix into a unitary matrix and a triangular matrix that tends to become smaller toward the upper left side. By performing this SQRD before LLLA, the amount of calculation in LLLA is reduced (see Non Patent Literature 5).
<Adaptive LLL-Algorithm (ALLL)>
An adaptive LLL-algorithm (ALLL) is known as an algorithm proposed as a method for reducing the amount of calculation in LLLA. ALLL is a technology based on MIMO with multiple temporally successive symbols. In this algorithm, rather than performing LLLA individually on channel matrices expressing the states of channels for the respective symbols, the result of LLLA for one previous symbol is utilized so as to reduce the amount of calculation in LLLA for the subsequent symbol (see Non Patent Literature 6).